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We give the definition of s-Vector control by using the complex power vector in the p-q plane to quantify the feasible operational region of battery energy storage system (BESS) and to find the optimal power set-point solution. The s-Vector control features in the avoidance of using costly optimization solvers to solve optimization models online which is also an execution time bottleneck in real-time control. The advantages of s-Vector control are fast and stable computational efficiency. We validate a s-Vector based real-time controller of BESS to provide frequency response and voltage support as ancillary services for the power grid. The objective is to maximize the utility of the BESS asset. We formulate the dynamic capability curve of the DC-AC converter and the security requirements of the battery cells as constrains of the control system. The initial power set-points are obtained based on the traditional droop control approach. Based on s-Vector control, a fast optimization solution algorithm is proposed to find the optimal power set-point and guarantee the security. According to the experimental validation in our 720 kVA / 560 kWh BESS on EPFL campus, we achieve 100 ms of refreshing the real-time control loop. As a benchmark, using optimization solver requires 200 ms to update the real-time control loop.
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Frequency response and voltage support are vital ancillary services for power grids. In this paper, we design and experimentally validate a real-time control framework for battery energy storage systems (BESSs) to provide ancillary services to power
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